import matplotlib.pyplot as plt
plt.figure(figsize=(10, 6))
plt.hist(df['gdp_per_capita'].dropna(), bins=20, color='skyblue')
plt.title('Distribution of GDP per Capita')
plt.xlabel('GDP per Capita')
plt.ylabel('Frequency')
plt.grid(True)
plt.show()
Presentation
2024-10-05
Slide 2
plt.figure(figsize=(10, 6))
plt.scatter(df['gdp_per_capita'], df['life_expectancy'], color='lightgreen', alpha=0.6)
plt.title('Scatter Plot of Life Expectancy vs GDP per Capita')
plt.xlabel('GDP per Capita (USD)')
plt.ylabel('Life Expectancy (Years)')
plt.grid(True)
plt.show()
Life expectancy varies significantly across countries, with developed countries such as Japan and Norway having life expectancies over 80 years.
Slide 3
plt.figure(figsize=(10, 6))
plt.scatter(df['gdp_per_capita'], df['unemployment_rate'], color='blue', alpha=0.7)
plt.title('Scatter Plot of Unemployment Rate vs GDP per Capita')
plt.xlabel('GDP per Capita (USD)')
plt.ylabel('Unemployment Rate (%)')
plt.grid(True)
plt.show()
Unemployment rates differ widely, with some developed countries exhibiting very low unemployment rates while other poor countries struggle with higher levels of unemployment.